Investigation into the optimization control technique of hydrogen-fueled engines based on genetic algorithms

An optimization control model which is about the relationship between power, economy, emission performances and operating parameters of hydrogen-fueled engines is established in the text, and optimality of the solutionʹs Pareto is realized through multi-objective optimization algorithm which is combined with Pareto rank and partial decision-making, and the optimization process of multi-objective is carried out parallelly in the searching process, the solution converges to the direction of decision partiality, and the convergence speed is improved; at the same time, dynamic adjustment of partial decision-making changes as the operating condition of hydrogen-fueled engines can be realized through weighting function, thus the control of multi-variable, multi-objective, multi-working status is unified to single-objective integrated optimal control technique. This develops a new avenue to solve the controlling problem of optimization objectiveʹs diversification and complication in hydrogen-fueled engines and improve the controlling precise further.